Is Precision Medicine a Mirage? Controversies and Challenges in Personalized Cancer Therapy

Nick Bilton, a Vanity Fair columnist, chronicled how Theranos drained its last drop of blood. Recently, the prominent online community BuzzFeed dropped another bombshell: 23andMe, the star genetic testing company, announced it would no longer perform next-generation DNA sequencing. In September, an article titled “The precision-oncology illusion” in Nature magazine directly pointed out that precision oncology is as much of a pipe dream as a time machine. From widespread acclaim to relentless criticism, is precision medicine truly feasible? VCBeat (WeChat ID: vcbeat) has summarized the article “Limits to Personalized Cancer Medicine” by Dr. Ian F. Tannock and colleagues from the University of Toronto, published in The New England Journal of Medicine, in hopes of finding answers.

Precision therapy, also known as personalized therapy, simply refers to the use of gene sequencing techniques to gain a deeper understanding of cancer at the molecular level. By distinguishing tumors from normal tissues based on genomic mutations in tumor cells, it enables targeted therapy against tumor cells, thereby aiming to prolong patient survival and improve their quality of life.

The rapid advancement of molecular pathology research and the comprehensiveness of diagnostics (ranging from gene sequencing to expression profiling and proteomics) have encouraged investment firms and cancer research centers to actively promote personalized cancer medicine. Precision therapies enable selective tumor control through pharmacological intervention, facilitating targeted drug delivery. Today, targeted therapy has become a critical component of cancer treatment, as exemplified by trastuzumab. While precision therapies benefit a subset of cancer patients, the duration of benefit is limited for the majority of those with metastatic disease, particularly given certain limitations in clinical efficacy.

In 2016, President Obama allocated $215 million to advance precision medicine, with $70 million designated for the National Cancer Institute (NCI) to support clinical research on personalized cancer medicine under the Cancer Moonshot initiative. Nearly all NCI-supported cancer research centers emphasize personalized medication, and the National Cancer Center has also implemented related programs.

Most institutions pursue independent research and clinical protocols; however, the results obtained from different projects are often similar, inevitably leading to a waste of resources, including patient resources, the time of clinicians and scientists, and funding. Some groups have formed alliances, such as the Lung Cancer Mutation Consortium, composed of 16 U.S. institutions conducting multi-gene mutation testing for lung and pancreatic cancers, and the UK’s Stratified Medicine Programme for rectal cancer, which has secured $6.6 million in funding to provide genomic analysis for colorectal cancer patients. Nevertheless, such collaborations remain rare. Fortunately, the U.S. government’s Cancer Moonshot Initiative offers more opportunities for collaboration.

Under ideal conditions, different cancer institutions emphasize distinct research approaches, thereby allocating resources across various fields. However, given the limited funding for research, resource waste in personalized medicine research may deprive other areas of necessary resources.

Randomized Controlled Trials of Precision Medicine: Comparing Treatment Efficacy Between Patients Receiving Targeted Therapy and Those Receiving Standard Care as the Ultimate Criterion for Evaluating Therapeutic Approaches. However, the results have been discouraging: although 30%–50% of patients were found to have tumor genetic variants through gene sequencing, only 3%–13% of them identified actionable treatment options via this approach. The randomized trial results showed that differences between groups were not significant, and the overall proportion of individuals achieving favorable responses was very low.

Multiple factors may limit the clinical efficacy of personalized medicine in current trials, including internal and external factors within clinical trials, as well as technical issues such as inadequate analysis of tumor specimens, which can hinder access to targeted therapies. Proponents argue that molecular profiling will ultimately improve, leading to the development of newer and better drugs that will enhance trial outcomes. However, Dr. Ian F. Tannock believes that limitations inherent to molecularly targeted agents, along with intratumoral heterogeneity driven by Darwinian evolution, will constrain the advancement of this technology.

An increasing variety of anticancer drugs are being developed to target different signaling pathways. Most molecularly targeted agents provide only partial inhibition of these pathways, necessitating combination therapies that often entail excessive drug toxicity.

Cancer cells generally possess strong adaptive capabilities and develop resistance to single-agent targeted therapies through mechanisms such as the upregulation of partially inhibited pathways, mutations at target sites, or activation of alternative pathways. While combination targeted therapies may inhibit these alternative pathways, the plasticity of signaling networks renders this approach impractical, as adaptive responses involve multiple other potential targets. Furthermore, combination targeted therapies often necessitate dose reductions, thereby further diminishing the inhibition of individual targets, while some combinations also lead to severe adverse reactions. These factors further limit their clinical application.

Molecular profiling of biopsy specimens has revealed substantial heterogeneity among multiple tumors, as well as between primary and metastatic lesions. Similarly, genomic sequencing of tumor biopsy samples from different anatomical sites in the same patient demonstrates considerable divergence. These findings support the Darwinian model of tumor evolution: captured cancer cell mutations serve as clonal markers, while distinct subclones persist within the tumor. Analysis of a single biopsy sample is not representative of other tumor regions; consequently, therapies guided by such limited sampling are inherently restricted in efficacy, as other active tumor cells harbor different mutations.

The prices of new cancer therapies available on the market are trending upward, with a disconnect between price and value (e.g., clinical efficacy). While expensive drugs such as imatinib and trastuzumab can be effective, the diminishing marginal returns of high-cost medications have shifted market resource allocation toward marketing rather than the pursuit of superior therapeutic outcomes. Precision medicine entails substantial costs. Although the cost-effectiveness of molecular analysis of tumor samples is showing positive trends, treatment with multiple molecularly targeted agents acting on aberrant pathways—whether administered concurrently or sequentially, depending on drug side effects—remains prohibitively expensive.

Precision oncology tailors treatment to the individual variability of cancer patients by targeting specific tumor mutations. This paradigm shifts away from traditional chemotherapy, moving from broad-spectrum cytotoxicity to precise targeting, thereby avoiding the side effects associated with damage to normal tissues. However, precision therapy is still in its nascent stage, and certain issues and limitations are inevitable, as theoretical models often assume idealized conditions.

However, these limitations do not warrant the abandonment of precision therapy. Dr. Ian F. Tannock suggests that small-scale, carefully designed trials should be conducted in the interim. Meanwhile, a clear message should be conveyed to patients: precision therapy is still in the clinical trial stage and has not yet achieved its intended objectives.

At the end of the article, Dr. Ian F. Tannock stated that research on precision therapy requires a deeper understanding of the inter-individual variations in molecular characteristics of tumors, as well as their associations with the natural history of the disease and treatment outcomes, thereby recognizing and overcoming these limitations through further investigation.